Prediction of Low Cost Housing Demand in Malaysia Using ARIMA Model

Abstract

Among the key challenges in construction industry sector faces are matching supply of and demand for affordable housing. It is very crucial to predict low-cost housing demand to match the demand and supply so that the government can plan the allocation of low cost housing based on the demand. In Johor, housing provision is very crucial due to urbanization. The supply of houses seems to be swamping the demand for luxury condos and houses especially in Johor Bharu. Thus the aim of this study is to predict low-cost housing demand in Johor, Malaysia using ARIMA model. Time series data on low-cost housing demand have been converted to Ln before develop the model. The actual data and forecasted data will be compared and validate using Mean Absolute Percentage Error (MAPE). After that, the results using ARIMA method will be compared with ANN method. The results show that MAPE analysis for ARIMA is 15.39% while ANN is 18.27%. It can be conclude that ARIMA model can forecast low cost housing demand in Johor quite good.